The field of financial advising includes various best practices. These best practices include identifying a client's financial goals (e.g. desired retirement age, desired annual income at retirement, desired vacation budget in retirement, desired estate value at death. etc.). In some application of general industry practices, but not all, clients are also asked to rank the stated goals in relative order of importance. Generally accepted “Best practices” also include identifying the client's risk tolerance and creating an investment allocation aimed at producing the highest return for the client's risk tolerance and then based on that allocation's expected return, calculating the savings needed to achieve the client's goals. In a conventional approach, to determine the client's risk tolerance a financial advisor uses a risk tolerance questionnaire or asks the client about their tolerance for investment risk defined by various mathematical methods like standard deviation, semi-variance or more commonly the largest level of annual portfolio losses with which the client could tolerate. This risk tolerance inquiry may be more nuanced, such as attempting to determine the amount of assets or percentage of value of a retirement plan that the client is willing to put into assets of various risks. Whatever method of attempting to identify the client's risk tolerance is used, the result of this inquiry is then used in recommending an allocation and related investments to an individual Often, investors are advised to accept a risk tolerance that is at or near the client's maximum endurance level for losses and or risk in their portfolio value.
Often the allocations are tested using a Monte Carlo simulation based on assumptions of the capital markets, samples of historical data, or both. The results of these simulations normally are used to convey a confidence level and/or a percentage risk of failure to achieve a desired income level, assets at retirement or any other of the client's identified goals.
In other approaches, such as wealth management, the client may define their risk tolerance and goals, and the advisor may provide advice regarding asset allocation relative to those risks and goals. Often, the financial advisor has the capability of running Monte Carlo simulations of future returns of various financial plans. These simulations can provide results which include a confidence level and therefore either an implicit or explicit percentage risk of failure to achieve a desired income level, assets at retirement, ending estate value, or other goals As before, the client may be advised to allocate their assets in the asset classes modeled and to invest in a variety of managed or unmanaged portfolio choices. Advisors may advise the client that actively managed investment alternatives can exceed the performance of the asset classes themselves (i.e. that they can outperform the market). Often, the fact that such actively managed investment alternatives also carry the risk of materially underperforming the market may not be adequately conveyed to the client by the advisor, or such risk may simply not be adequately understood by the investor, or the advisor and that uncertainty is not normally considered in the confidence calculation which normally relies on the simulated performance of only asset classes to consider the effect of the uncertainty of asset class returns. Therefore the additional uncertainty that active management risks potentially underperforming the various asset classes is normally not considered. It is ignored and therefore renders the confidence level of such simulations in essence meaningless.
Typical disclaimers used in the industry, which are in significant part intended to provide legal safe harbor to the advisor (e.g. “past performance is not a guarantee of future results”), may not adequately convey to the client the nature of the risk in actively managed investments This is because normally the confidence calculation was based on the uncertainty of asset class returns; but actively managed portfolios may equal, exceed or under-perform their respective asset classes thereby introducing additional uncertainty absent from the confidence calculation. Therefore, what that confidence number means may or may not be fully understood by the client, or the financial advisor for that matter.
Furthermore, current approaches often involve periodic reviews of the performance of the client's portfolio. As part of the review the client may be provided with a chart, graph or other representation of how their portfolio has performed relative to the various capital markets (i.e. the client's optimal allocation to various asset classes for their risk tolerance). If performance was lower than expected or assumed by the advisor in the original consultation, the client may be advised to change investment managers, wait for a more favorable environment for the manager's “style” or perhaps increase the amount contributed to the portfolio. Alternatively, the client may be advised to eliminate one or more of the lowest-ranked goals. If, on the other hand, performance was better than expected, the client will typically not be advised to reduce the amount contributed to the portfolio, even if such a reduction based on the superior performance is possible (i.e., maintaining the original “risk tolerance” level).
Thus, there is a need in the industry for a new method of financial advising that eliminates the substantial uncertainties associated with investing the client's assets in actively managed investment alternatives, does not position clients at their maximum tolerance for risk if there are more appealing choices the client could make that enable them to have sufficient confidence of achieving the goals they value and thus eliminates the aforementioned difficulties associated with conveying such risks to the client. Furthermore, there is a need to provide clients with periodic feedback that does not simply chart how their portfolio has performed relative to the market, but rather provides clients with a practical understanding of the concrete impact that the performance of their portfolio has had their desired goals. There is also a need for a more nuanced approach to evaluating client goals, which comprises more than a simple linear ranking of goals, but rather which interrelates all of the client's goals so that the client can make more informed and satisfying choices about their goals in light of the performance of their portfolio. As a result, the inventive system will be more highly valued by clients compared to current approaches.